Application Guide
How to Apply for Staff ML Platform Engineer
at Afresh Technologies
🏢 About Afresh Technologies
Afresh Technologies is an AI-driven platform specifically focused on reducing food waste in the fresh food supply chain, having already prevented millions of pounds of waste annually. What makes Afresh unique is its mission-driven approach combining cutting-edge technology with tangible environmental impact, creating a rare opportunity to work on ML infrastructure that directly addresses a critical global sustainability challenge.
About This Role
As a Staff ML Platform Engineer at Afresh, you'll be building and maintaining the foundational infrastructure that powers all machine learning solutions across the company, enabling teams to develop, deploy, and scale robust ML models more efficiently. This role is particularly impactful because you'll be working on critical infrastructure that directly accelerates innovation for all ML and Applied Science teams, directly contributing to the company's mission of reducing food waste through technology.
💡 A Day in the Life
A typical day might involve collaborating with ML engineers to understand their infrastructure needs, designing and implementing shared components that accelerate model development, and optimizing platform performance to ensure reliable scaling of ML solutions. You'd likely spend time mentoring junior engineers while working on critical infrastructure improvements that directly enable faster innovation across Afresh's ML and Applied Science teams.
🚀 Application Tools
🎯 Who Afresh Technologies Is Looking For
- Has 7+ years of professional software development experience with a proven track record of shipping high-quality, scalable applications and services in production environments
- Possesses deep experience collaborating with machine learning engineers, data scientists, or applied scientists on large-scale software projects involving ML models, not just theoretical knowledge
- Demonstrates technical leadership experience with a track record of mentoring junior engineers and elevating platform performance, reliability, and scalability
- Has experience with ML infrastructure tooling, shared components, and services that enable ML model development and deployment at scale
📝 Tips for Applying to Afresh Technologies
Highlight specific examples where you've built or maintained foundational infrastructure that powered ML solutions, quantifying the impact on team productivity or system performance
Demonstrate your experience working collaboratively with ML engineers or data scientists by describing specific cross-functional projects and your role in enabling their work
Emphasize any experience with sustainability, food systems, or mission-driven tech companies, as Afresh specifically values candidates aligned with their environmental impact mission
Showcase your technical leadership experience with concrete examples of mentoring junior engineers and driving platform improvements that elevated reliability and scalability
Tailor your resume to show progression in ML platform or infrastructure roles, highlighting how your work enabled other teams to innovate faster and deliver impact
✉️ What to Emphasize in Your Cover Letter
['Your specific experience building and maintaining foundational infrastructure that powers machine learning solutions, with quantifiable results', 'Examples of successful collaboration with ML engineers or data scientists on large-scale projects and how you enabled their work', "Why you're particularly drawn to Afresh's mission of reducing food waste and how your skills align with their sustainability focus", 'Your approach to technical leadership and mentoring, specifically in the context of elevating platform performance and reliability']
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Afresh's specific approach to reducing food waste in the fresh food supply chain and their current ML applications
- → The company's technology stack and any public information about their ML platform architecture
- → Recent news about Afresh's partnerships, funding, or expansion in the Canadian market
- → The fresh food supply chain challenges and how ML solutions specifically address food waste reduction
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Focusing only on ML model development experience without emphasizing infrastructure and platform engineering expertise
- Presenting generic software engineering experience without specific examples of working with ML teams or building ML-focused infrastructure
- Failing to demonstrate understanding of Afresh's mission and how ML platform engineering specifically contributes to reducing food waste
📅 Application Timeline
This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.
Typical hiring timeline:
Application Review
1-2 weeks
Initial Screening
Phone call or written assessment
Interviews
1-2 rounds, usually virtual
Offer
Congratulations!
Ready to Apply?
Good luck with your application to Afresh Technologies!